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Amazon Lex launches configurable voice activity detection sensitivity

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Amazon Lex now provides three VAD sensitivity levels that can be configured for each bot locale: Default, High, and Maximum. The Default setting is suitable for most environments with typical background noise levels. High is designed for environments with consistent but moderate noise levels, such as busy offices or retail spaces. Maximum provides the highest tolerance for very noisy environments such as manufacturing floors, construction sites, or outdoor locations with significant ambient noise. You can configure VAD sensitivity when creating or updating a bot locale in the Amazon Connect’s Conversational AI designer.

This feature is available in all AWS commercial regions where Amazon Connect and Lex operate. To learn more, visit the Amazon Lex documentation or explore the Amazon Connect website to learn how Amazon Connect and Amazon Lex deliver seamless end-customer self-service experiences.

Amazon SageMaker HyperPod now validates service quotas before creating clusters on console

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Amazon SageMaker HyperPod console now validates service quotas for your AWS account before initiating cluster creation, enabling you to confirm sufficient quota availability before provisioning begins. SageMaker HyperPod helps you provision resilient clusters for running AI/ML workloads and developing state-of-the-art models such as large language models (LLMs), diffusion models, and foundation models (FMs).

When creating large-scale AI/ML clusters, you need to ensure your account has sufficient quotas for instances, storage, and networking resources, but quota validation previously required manual checks across multiple AWS services, often resulting in failed cluster creation attempts and wasted time if you miss requesting quota limit increases. The new quota validation capability in the SageMaker HyperPod console automatically checks your account-level quotas against your cluster configuration, including instance type limits, EBS volume sizes, and VPC-related quotas when creating new resources. The validation displays a clear table showing expected utilization, applied quota values, and compliance status for each quota. When quotas may be exceeded, you receive a warning alert with direct links to the Service Quotas console to request increases.

This feature is available in all AWS Regions where Amazon SageMaker HyperPod is supported. For a complete list of service quota validation checks performed, refer to the Amazon SageMaker HyperPod User Guide .

Amazon MSK Connect is now available in three additional AWS Regions

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Amazon MSK Connect is now available in three additional AWS Regions: Asia Pacific (New Zealand), AWS GovCloud (US-East), and AWS GovCloud (US-West).

MSK Connect enables you to run fully managed Kafka Connect clusters with Amazon Managed Streaming for Apache Kafka (Amazon MSK). With a few clicks, MSK Connect allows you to easily deploy, monitor, and scale connectors that move data in and out of Apache Kafka and Amazon MSK clusters from external systems such as databases, file systems, and search indices. MSK Connect eliminates the need to provision and maintain cluster infrastructure. Connectors scale automatically in response to increases in usage and you pay only for the resources you use. With full compatibility with Kafka Connect, it is easy to migrate workloads without code changes. MSK Connect will support both Amazon MSK-managed and self-managed Apache Kafka clusters.

You can get started with MSK Connect from the Amazon MSK console or the Amazon CLI. With this launch, MSK Connect is now available in thirty eight AWS Regions. To get started visit, the MSK Connect product page , pricing page , and the Amazon MSK Developer Guide .

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